Corrosion cost the Air Force over $5 Billion and the Navy more than $8.6 billion in 2023, not including costs related to support equipment and vehicles. Understanding materials corrosion is a critical step in materials selection and qualification for aerospace components, vehicles, oil and gas pipelines and facilities, and other infrastructure. UDRI’s corrosion testing laboratories assist partners in characterizing materials for use in multiple applications while understanding how to cost-effectively maintain and support critical systems in the harshest environments.

Cost of Corrosion in 2023

$5 Billion

US Air Force

$8.6 Billion

US Navy

Testing & Qualification of Coatings

UDRI expert scientists and engineers provide research, development, testing, evaluation, qualification, integration and sustainment planning for advanced aerospace and industrial materials.

Areas of Expertise

Coatings testing and qualification
Corrosion science
Erosion phenomena and erosion-resistant materials
Test method development
Materials and processes improvement and integration activities to better predict the payoff of improved performance that results from alternate designs
Evaluation of materials and operational environment to inform adoption and sustainment requirements

${ Large military aircraft being washed to prevent corrosion. }

Proven Partnership & Support

UDRI has been supporting US Air Force corrosion, erosion and sustainment initiatives for over 23 years, developing unique experience in operating and testing erosion equipment such as the Hot Erosion Rig (HER) and the Supersonic Rain Erosion Rig (SuRE) at Wright-Patterson Air Force Base.

UDRI has continually maintained ISO/IEC 17025 accreditation and SAE AS-5505 certification since 2001. These certifications cover all testing required to qualify of Air Force Outer Mold Line (OML) and Inner Mold Line (IML) coatings. Our team of experienced professionals and expert technicians solve M&P, coating, corrosion, specialty material and erosion challenges, help develop and integrate novel, improved and cost-saving materials, methods and equipment, and perform research resulting in significant cost savings and long-lasting impacts.

UDRI’s Machine Learning (ML) and Data Analytics teams have worked together to develop guided tools for Air Force customers. These tools consist of interactive dashboards using machine learning and large language models (LLM) leveraging aircraft maintenance data to identify special areas of interest for corrosion stakeholders. This allows for targeted efforts to address consistent, costly corrosion problems across multiple airframes that directly impact maintenance manhours and aircraft downtime.

UDRI is a key stakeholder in corrosion modeling efforts taking place across the Department of Defense aimed at developing comprehensive data sets for modeling and simulation for corrosion planning and has previously served as a validation test bed for other modeling efforts.

Machine Learning Algorithms

UDRI-developed machine learning algorithms improve user awareness of available data, suggest areas for further investigation and make connections between users and information to ensure analyses have more breadth and depth than a single user working alone.

Vision-based systems to verify the line-tool position and orientation
Atomization characterization on shadowgraph images for spray applications

Data science and machine learning approaches for optimizing flight design parameters
Planning and content recommendation systems using combinations of expert systems with ML models

Maintenance log text correction, standardization and correlation using an ensemble of probabilistic models, supervised learning and unsupervised learning
Video summarization and organization by leveraging computer vision, audio processing and natural language processing technologies

Detection and characterization of Coordinate Measuring Machine (CMM) probes
Detection of distortions and defects in additive manufacturing processes from in-situ tomography, thermal or electro-optic data

Supply chain risk prediction using a suite of ML models
Probabilistic learning for the prediction of solar energy production

Testing, Characterization & Evaluation

Our expert research and engineering teams conduct comprehensive suites of testing, characterization and inspection scenarios to evaluate the structural integrity and maintenance of materials, components and structures.

Materials Testing & Characterization

UDRI provides high-rate testing services using Digital Image Correlation (DIC), providing full-filed strain measurements to failure at speeds up to 800”/sec. We house a proprietary crack growth monitoring system allowing for 24/7 testing without interruption all while monitoring and allowing for crack propagation measurements.

Impact Physics

UDRI’s Impact Physics researchers generate material property data from quasi-static to strain rates approaching 5,000/sec. Split Hopkinson bars are used to determine compressive, tensile or shear stress-strain behavior of both metallic alloys and nonmetallic materials including ceramics, glass, plastics, foam and concrete. Shock wave phenomena are studied using flyer plate impact experiments. These experiments have enabled researchers to develop constitutive models and Hugoniot Elastic Limit (HEL) Curves. Testing can also be performed over a range of temperatures.

Nondestructive Inspections

UDRI’s Nondestructive Evaluation (NDE) experience in robotics and automation provides the capability to enhance existing experimental systems, as well as design the next generation of automated systems for laboratory, industrial or depot use. Our experience in image and signal processing includes a variety of data formats obtained from NDE sensors and imaging systems.

The appearance of U.S. Department of Defense (DoD) visual information does not imply or constitute DoD endorsement.

Coatings & Corrosion Management

The Impact of Corrosion